# Staff Compute & Storage Capacity Planner

**Company:** [Crusoe](https://hotfix.jobs/companies/crusoe)
**Location:** San Francisco, CA, Sunnyvale, CA, Seattle, WA
**Role:** Business Operations
**Salary:** $195k – $235k/yr
**Experience:** 3+ years
**Skills:** Infrastructure Capacity Planning, Compute Capacity Planning, Storage Capacity Planning, Demand Forecasting, Cpu Sizing, File Storage, Object Storage, Block Storage, Infrastructure Systems Engineering, Technical Product Management, Cross-Functional Collaboration, Data Mining, Automation, Capacity Modeling
**Posted:** 2026-06-25

> Own multi-quarter capacity planning and optimization for compute (CPU) and multi-tier storage (File, Object, Block) across Crusoe Cloud infrastructure. Partner with engineering, finance, and supply chain to forecast demand, maximize utilization, and align hardware deployment with business and sustainability goals.

## Job Description

## What You'll Be Working On

- **End-to-End Capacity Modeling**: Own and manage the multi-quarter capacity plans and allocation models for core infrastructure resources across Compute (CPUs) and multi-tiered Storage platforms (File, Object, and Block arrays).
- **Demand Forecasting & Signal Analysis**: Analyze demand signals, historical workload profiles, customer usage shifts, and product roadmaps to build highly precise resource consumption forecasts to guide strategic hardware placement strategies.
- **Cross-Functional Collaboration**: Partner closely with Sales, Storage Engineering, Server Hardware Engineering, SRE, Product, Finance, and Supply Chain to translate high-level product forecasts into physically deployed hardware allocations while navigating global procurement lead times.
- **Efficiency & Financial Optimization**: Interface directly with Finance and Product to tightly balance structural cost efficiency, infrastructure unit economics, depreciation schedules, and hardware utilization targets against technical availability cushions.
- **Automation Requirements**: Define operational metrics, establish planning baseline standards, and partner with Software Engineering teams to architect, automate, and implement automated capacity workflows and real-time visualization dashboards.
- **Data Mining & Validation**: Perform complex data mining and verification across raw hardware usage metrics, asset management databases, and financial billing pipelines to guarantee maximum structural accuracy in capital efficiency models.

## What You'll Bring to the Team

- **Proven Capacity Domain Expertise**: 3+ years of direct experience in Infrastructure Capacity Planning, Infrastructure Systems Engineering, or Technical Product Management with heavy exposure to compute and storage.
- **Deep Hardware & Architecture Familiarity**: Demonstrated foundational technical knowledge of enterprise server configurations, CPU sizing/benchmarking, and storage across File, Object, and Block storage infrastructures.
- **Hyper-Growth Experience**: Experience working inside high-growth, fast-paced public cloud environments or massively distributed systems topologies.
- **Excellent Communication**: Strong structured narrative delivery, documentation, and cross-functional negotiation skills to successfully bridge alignment across engineering technicalities and business/financial constraints.
- **Education**: Bachelor’s or Master's degree in Computer Engineering, Computer Science, Operations Research, Mathematics, Data Science, or an equivalent technical/quantitative field.

## Bonus Points

- Experience building or defining foundational product requirements for custom in-house software automation tools used for machine-level monitoring, resource provisioning, or automated capacity modeling.
- Willingness and capacity to scale scope into specialized GPU clusters and cutting-edge accelerated AI computing fabrics as the underlying infrastructure footprint expands.

## Compensation

Compensation will be paid in the range of up to $195,000 - $235,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.

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